Frequently Asked Questions

This page exists to answer common questions about the Rust programming language. It is not a complete guide to the language, nor is it a tool for teaching the language. It is a reference to answer oft-repeated questions people in the Rust community encounter, and to clarify the reasoning behind some of Rust's design decisions.

If there is some common or important question you feel is wrongly left unanswered here, feel free to help us fix it.

No. Rust started as Graydon Hoare’s part-time side project in 2006 and remained so for over 3 years. Mozilla got involved in 2009 once the language was mature enough to run basic tests and demonstrate its core concepts. Though it remains sponsored by Mozilla, Rust is developed by a diverse community of enthusiasts from many different places around the world. The Rust Team is composed of both Mozilla and non-Mozilla members, and rust on GitHub has had over 1,900 unique contributors so far.

As far as project governance goes, Rust is managed by a core team that sets the vision and priorities for the project,
guiding it from a global perspective. There are also subteams to guide and foster development of particular areas of interest, including the core language, the compiler, Rust libraries, Rust tools, and moderation of the official Rust communities. Designs in each of these areas are advanced through an RFC process. For changes which do not require an RFC, decisions are made through pull requests on the rustc repository.

The easiest way to try Rust is through the playpen, an online app for writing and running Rust code. If you want to try Rust on your system, install it and go through the Guessing Game tutorial in the book.

Rust started with a goal of creating a safe but usable systems programming language. In pursuit of this goal it explored a lot of ideas, some of which it kept (lifetimes, traits) while others were discarded (the typestate system, green threading). Also, in the run up to 1.0 a lot of the standard library was rewritten as early designs were updated to best use Rust’s features and provide quality, consistent cross-platform APIs. Now that Rust has reached 1.0, the language is guaranteed to be “stable”; and while it may continue to evolve, code which works on current Rust should continue to work on future releases.

Rust’s language versioning follows SemVer, with backwards incompatible changes of stable APIs only allowed in minor versions if those changes fix compiler bugs, patch safety holes, or change dispatch or type inference to require additional annotation. More detailed guidelines for minor version changes are available as approved RFCs for both the language and standard library.

Rust maintains three “release channels”: stable, beta, and nightly. Stable and beta are updated every six weeks, with the current nightly becoming the new beta, and the current beta becoming the new stable. Language and standard library features marked unstable or hidden behind feature gates may only be used on the nightly release channel. New features land as unstable, and are “ungated” once approved by the core team and relevant subteams. This approach allows for experimentation while providing strong backwards-compatibility guarantees for the stable channel.

No, you cannot. Rust works hard to provide strong guarantees about the stability of the features provided on the beta and stable channels. When something is unstable, it means that we can’t provide those guarantees for it yet, and don’t want people relying on it staying the same. This gives us the opportunity to try changes in the wild on the nightly release channel, while still maintaining strong guarantees for people seeking stability.

Things stabilize all the time, and the beta and stable channels update every six weeks, with occasional fixes accepted into beta at other times. If you’re waiting for a feature to be available without using the nightly release channel, you can locate its tracking issue by checking the B-unstable tag on the issue tracker.

“Feature gates” are the mechanism Rust uses to stabilize features of the compiler, language, and standard library. A feature that is “gated” is accessible only on the nightly release channel, and then only when it has been explicitly enabled through #[feature] attributes or the -Z unstable-options command line argument. When a feature is stabilized it becomes available on the stable release channel, and does not need to be explicitly enabled. At that point the feature is considered “ungated”. Feature gates allow developers to test experimental features while they are under development, before they are available in the stable language.

This is partly due to preference of the original developer (Graydon), and partly due to the fact that languages tend to have a wider audience and more diverse set of possible embeddings and end-uses than products such as web browsers. We’d like to appeal to as many of those potential contributors as possible.

Performance

Fast! Rust is already competitive with idiomatic C and C++ in a number of benchmarks (like the Benchmarks Game and others).

Like C++, Rust takes zero-cost abstractions as one of its core principles: none of Rust’s abstractions impose a global performance penalty, nor is there overhead from any runtime system in the traditional sense.

Given that Rust is built on LLVM and strives to resemble Clang from LLVM’s perspective, any LLVM performance improvements also help Rust. In the long run, the richer information in Rust’s type system should also enable optimizations that are difficult or impossible for C/C++ code.

By avoiding GC, Rust can offer numerous benefits: predictable cleanup of resources, lower overhead for memory management, and essentially no runtime system. All of these traits make Rust lean and easy to embed into arbitrary contexts, and make it much easier to integrate Rust code with languages that have a GC.

For when single ownership does not suffice, Rust programs rely on the standard reference-counting smart pointer type, Rc, and its thread-safe counterpart, Arc, instead of GC.

We are however investigating optional garbage collection as a future
extension. The goal is to enable smooth integration with
garbage-collected runtimes, such as those offered by the
Spidermonkey
and V8 JavaScript engines.
Finally, some people have investigated implementing
pure Rust garbage collectors
without compiler support.

Code translation and optimizations. Rust provides high level abstractions that compile down into efficient machine code, and those translations take time to run, especially when optimizing.

But Rust’s compilation time is not as bad as it may seem, and there is reason to believe it will improve. When comparing projects of similar size between C++ and Rust, compilation time of the entire project is generally believed to be comparable. The common perception that Rust compilation is slow is in large part due to the differences in the compilation model between C++ and Rust: C++’s compilation unit is the file, while Rust’s is the crate, composed of many files. Thus, during development, modifying a single C++ file can result in much less recompilation than in Rust. There is a major effort underway to refactor the compiler to introduce incremental compilation, which will provide Rust the compile time benefits of C++’s model.

Aside from the compilation model, there are several other aspects of Rust’s language design and compiler implementation that affect compile-time performance.

First, Rust has a moderately-complex type system, and must spend a non-negligible amount of compile time enforcing the constraints that make Rust safe at runtime.

Secondly, the Rust compiler suffers from long-standing technical debt, and notably generates poor-quality LLVM IR which LLVM must spend time “fixing.” The addition of a new internal representation called MIR to the Rust compiler offers the potential to perform more optimizations and improve the quality of LLVM IR generated, but this work has not yet occured.

Thirdly, Rust’s use of LLVM for code generation is a double-edged sword: while it enables Rust to have world-class runtime performance, LLVM is a large framework that is not focused on compile-time performance, particularly when working with poor-quality inputs.

Finally, while Rust’s preferred strategy of monomorphising generics (ala C++) produces fast code, it demands that significantly more code be generated than other translation strategies. Rust programmers can use trait objects to trade away this code bloat by using dynamic dispatch instead.

While SipHash demonstrates competitive performance in many cases, one case where it is notably slower than other hashing algorithms is with short keys, such as integers. This is why Rust programmers often observe slow performance with HashMap. The FNV hasher is frequently recommended for these cases, but be aware that it does not have the same collision-resistance properties as SipHash.

There is, but it’s only available on the nightly release channel. We ultimately plan to build a pluggable system for integrated benchmarks, but in the meantime, the current system is considered unstable.

Not generally, no. Tail-call optimization may be done in limited circumstances, but is not guaranteed. As the feature has always been desired, Rust has a keyword (become) reserved, though it is not clear yet whether it is technically possible, nor whether it will be implemented. There was a proposed extension that would allow tail-call elimination in certain contexts, but it is currently postponed.

Not in the typical sense used by languages such as Java, but parts of the Rust standard library can be considered a “runtime”, providing a heap, backtraces, unwinding, and stack guards. There is a small amount of initialization code that runs before the user’s main function. The Rust standard library additionally links to the C standard library, which does similar runtime initialization. Rust code can be compiled without the standard library, in which case the runtime is roughly equivalent to C’s.

Whereas C requires mandatory parentheses for if-statement conditionals but leaves brackets optional, Rust makes the opposite choice for its if-expressions. This keeps the conditional clearly separate from the body and avoids the hazard of optional brackets, which can lead to easy-to-miss errors during refactoring, like Apple’s goto fail bug.

Rust’s overall design preference is for limiting the size of the language while enabling powerful libraries. While Rust does provide initialization syntax for arrays and string literals, these are the only collection types built into the language. Other library-defined types, including the ubiquitous Vec collection type, use macros for initialization like the vec! macro.

This design choice of using Rust’s macro facilities to initialize collections will likely be extended generically to other collections in the future, enabling simple initialization of not only HashMap and Vec, but also other collection types such as BTreeMap. In the meantime, if you want a more convenient syntax for initializing collections, you can create your own macro to provide it.

Rust is a very expression-oriented language, and “implicit returns” are part of that design. Constructs like ifs, matches, and normal blocks are all expressions in Rust. For example, the following code checks if an i64 is odd, returning the result by simply yielding it as a value:

fnis_odd(x:i64)->bool{ifx%2!=0{true}else{false}}

Although it can be simplified even further like so:

fnis_odd(x:i64)->bool{x%2!=0}

In each example, the last line of the function is the return value of that function. It is important to note that if a function ends in a semicolon, its return type will be (), indicating no returned value. Implicit returns must omit the semicolon to work.

Explicit returns are only used if an implicit return is impossible because you are returning before the end of the function’s body. While each of the above functions could have been written with a return keyword and semicolon, doing so would be unnecessarily verbose, and inconsistent with the conventions of Rust code.

In Rust, declarations tend to come with explicit types, while actual code has its types inferred. There are several reasons for this design:

Mandatory declaration signatures help enforce interface stability at both the module and crate level.

Signatures improve code comprehension for the programmer, eliminating the need for an IDE running an inference algorithm across an entire crate to be able to guess at a function’s argument types; it’s always explicit and nearby.

Mechanically, it simplifies the inference algorithm, as inference only requires looking at one function at a time.

First, if every possibility is covered by the match, adding variants to the enum in the future will cause a compilation failure, rather than an error at runtime. This type of compiler assistance makes fearless refactoring possible in Rust.

Second, exhaustive checking makes the semantics of the default case explicit: in general, the only safe way to have a non-exhaustive match would be to panic the thread if nothing is matched. Early versions of Rust did not require match cases to be exhaustive and it was found to be a great source of bugs.

It is easy to ignore all unspecified cases by using the _ wildcard:

matchval.do_something(){Cat(a)=>{/* ... */}_=>{/* ... */}}

Numerics

The choice of which to use is dependent on the purpose of the program.

If you are interested in the greatest degree of precision with your floating point numbers, then prefer f64. If you are more interested in keeping the size of the value small or being maximally efficient, and are not concerned about the associated inaccuracy of having fewer bits per value, then f32 is better. Operations on f32 are usually faster, even on 64-bit hardware. As a common example, graphics programming typically uses f32 because it requires high performance, and 32-bit floats are sufficient for representing pixels on the screen.

Floats can be compared with the ==, !=, <, <=, >, and >= operators, and with the partial_cmp() function. == and != are part of the PartialEq trait, while <, <=, >, >=, and partial_cmp() are part of the PartialOrd trait.

Floats cannot be compared with the cmp() function, which is part of the Ord trait, as there is no total ordering for floats. Furthermore, there is no total equality relation for floats, and so they also do not implement the Eq trait.

There is no total ordering or equality on floats because the floating-point value NaN is not less than, greater than, or equal to any other floating-point value or itself.

Because floats do not implement Eq or Ord, they may not be used in types whose trait bounds require those traits, such as BTreeMap or HashMap. This is important because these types assume their keys provide a total ordering or total equality relation, and will malfunction otherwise.

There is a crate that wraps f32 and f64 to provide Ord and Eq implementations, which may be useful in certain cases.

There are two ways: the as keyword, which does simple casting for primitive types, and the Into and From traits, which are implemented for a number of type conversions (and which you can implement for your own types). The Into and From traits are only implemented in cases where conversions are lossless, so for example, f64::from(0f32) will compile while f32::from(0f64) will not. On the other hand, as will convert between any two primitive types, truncating values as necessary.

Preincrement and postincrement (and the decrement equivalents), while convenient, are also fairly complex. They require knowledge of evaluation order, and often lead to subtle bugs and undefined behavior in C and C++. x = x + 1 or x += 1 is only slightly longer, but unambiguous.

Strings

Usually, you can pass a reference to a String or Vec<T> wherever a slice is expected.
Using Deref coercions, Strings and Vecs will automatically coerce to their respective slices when passed by reference with & or & mut.

Methods implemented on &str and &[T] can be accessed directly on String and Vec<T>. For example, some_string.trim() will work even though trim is a method on &str and some_string is a String.

In some cases, such as generic code, it’s necessary to convert manually. Manual conversions can be achieved using the slicing operator, like so: &my_vec[..].

String is an owned buffer of UTF-8 bytes allocated on the heap. Mutable Strings can be modified, growing their capacity as needed. &str is a fixed-capacity “view” into a String allocated elsewhere, commonly on the heap, in the case of slices dereferenced from Strings, or in static memory, in the case of string literals.

&str is a primitive type implemented by the Rust language, while String is implemented in the standard library.

You cannot. At least not without a firm understanding of what you mean by “character”, and preprocessing the string to find the index of the desired character.

Rust strings are UTF-8 encoded. A single visual character in UTF-8 is not necessarily a single byte as it would be in an ASCII-encoded string. Each byte is called a “code unit” (in UTF-16, code units are 2 bytes; in UTF-32 they are 4 bytes). “Code points” are composed of one or more code units, and combine in “grapheme clusters” which most closely approximate characters.

Thus, even though you may index on bytes in a UTF-8 string, you can’t access the ith code point or grapheme cluster in constant time. However, if you know at which byte that desired code point or grapheme cluster begins, then you can access it in constant time. Functions including str::find() and regex matches return byte indices, facilitating this sort of access.

The str type is UTF-8 because we observe more text in the wild in this encoding – particularly in network transmissions, which are endian-agnostic – and we think it’s best that the default treatment of I/O not involve having to recode codepoints in each direction.

This does mean that locating a particular Unicode codepoint inside a string is an O(n) operation, although if the starting byte index is already known then they can be accessed in O(1) as expected. On the one hand, this is clearly undesirable; on the other hand, this problem is full of trade-offs and we’d like to point out a few important qualifications:

Scanning a str for ASCII-range codepoints can still be done safely byte-at-a-time. If you use .as_bytes(), pulling out a u8 costs only O(1) and produces a value that can be cast and compared to an ASCII-range char. So if you’re (say) line-breaking on '\n', byte-based treatment still works. UTF-8 was well-designed this way.

Most “character oriented” operations on text only work under very restricted language assumptions such as “ASCII-range codepoints only”. Outside ASCII-range, you tend to have to use a complex (non-constant-time) algorithm for determining linguistic-unit (glyph, word, paragraph) boundaries anyway. We recommend using an “honest” linguistically-aware, Unicode-approved algorithm.

The char type is UTF-32. If you are sure you need to do a codepoint-at-a-time algorithm, it’s trivial to write a type wstr = [char], and unpack a str into it in a single pass, then work with the wstr. In other words: the fact that the language is not “decoding to UTF32 by default” shouldn’t stop you from decoding (or re-encoding any other way) if you need to work with that encoding.

Rust has four pairs of string types, each serving a distinct purpose. In each pair, there is an “owned” string type, and a “slice” string type. The organization looks like this:

“Slice” type

“Owned” type

UTF-8

str

String

OS-compatible

OsStr

OsString

C-compatible

CStr

CString

System path

Path

PathBuf

Rust’s different string types serve different purposes. String and str are UTF-8 encoded general-purpose strings. OsString and OsStr are encoded according to the current platform, and are used when interacting with the operating system. CString and CStr are the Rust equivalent of strings in C, and are used in FFI code, and PathBuf and Path are convenience wrappers around OsString and OsStr, providing methods specific to path manipulation.

If the function needs an owned string, but wants to accept any type of string, use an Into<String> bound.

If the function needs a string slice, but wants to accept any type of string, use an AsRef<str> bound.

If the function does not care about the string type, and wants to handle the two possibilities uniformly, use Cow<str> as the input type.

Using Into<String>

In this example, the function will accept both owned strings and string slices, either doing nothing or converting the input into an owned string within the function body. Note that the conversion needs to be done explicitly, and will not happen otherwise.

fnaccepts_both<S:Into<String>>(s:S){lets=s.into();// This will convert s into a `String`.// ... the rest of the function}

Using AsRef<str>

In this example, the function will accept both owned strings and string slices, either doing nothing or converting the input into a string slice. This can be done automatically by taking the input by reference, like so:

fnaccepts_both<S:AsRef<str>>(s:&S){// ... the body of the function}

Using Cow<str>

In this example, the function takes in a Cow<str>, which is not a generic type but a container, containing either an owned string or string slice as needed.

Collections

If your reason for implementing these data structures is to use them for other programs, there’s no need, as efficient implementations of these data structures are provided by the standard library.

If, however, your reason is simply to learn, then you will likely need to dip into unsafe code. While these data structures can be implemented entirely in safe Rust, the performance is likely to be worse than it would be with the use of unsafe code. The simple reason for this is that data structures like vectors and linked lists rely on pointer and memory operations that are disallowed in safe Rust.

For example, a doubly-linked list requires that there be two mutable references to each node, but this violates Rust’s mutable reference aliasing rules. You can solve this using Weak<T>, but the performance will be poorer than you likely want. With unsafe code you can bypass the mutable reference aliasing rule restriction, but must manually verify that your code introduces no memory safety violations.

Rust for loops call into_iter() (defined on the IntoIterator trait) for whatever they’re iterating over. Anything implementing the IntoIterator trait may be looped over with a for loop. IntoIterator is implemented for &Vec and &mut Vec, causing the iterator from into_iter() to borrow the contents of the collection, rather than moving/consuming them. The same is true for other standard collections as well.

If a moving/consuming iterator is desired, write the for loop without & or &mut in the iteration.

If you need direct access to a borrowing iterator, you can usually get it by calling the iter() method.

You don’t necessarily have to. If you’re declaring an array directly, the size is inferred based on the number of elements. But if you’re declaring a function that takes a fixed-size array, the compiler has to know how big that array will be.

One thing to note is that currently Rust doesn’t offer generics over arrays of different size. If you’d like to accept a contiguous container of a variable number of values, use a Vec or slice (depending on whether you need ownership).

These are different terms for the same thing. In all cases, it means the value has been moved to another owner, and moved out of the possession of the original owner, who can no longer use it. If a type implements the Copy trait, the original owner’s value won’t be invalidated, and can still be used.

If a type implements the Copy trait, then it will be copied when passed to a function. All numeric types in Rust implement Copy, but struct types do not implement Copy by default, so they are moved instead. This means that the struct can no longer be used elsewhere, unless it is moved back out of the function via the return.

This error means that the value you’re trying to use has been moved to a new owner. The first thing to check is whether the move in question was necessary: if it moved into a function, it may be possible to rewrite the function to use a reference, rather than moving. Otherwise if the type being moved implements Clone, then calling clone() on it before moving will move a copy of it, leaving the original still available for further use. Note though that cloning a value should typically be the last resort since cloning can be expensive, causing further allocations.

If the moved value is of your own custom type, consider implementing Copy (for implicit copying, rather than moving) or Clone (explicit copying). Copy is most commonly implemented with #[derive(Copy, Clone)] (Copy requires Clone), and Clone with #[derive(Clone)].

If none of these are possible, you may want to modify the function that acquired ownership to return ownership of the value when the function exits.

The borrow checker applies only a few rules, which can be found in the Rust book’s section on borrowing, when evaluating Rust code. These rules are:

First, any borrow must last for a scope no greater than that of the owner. Second, you may have one or the other of these two kinds of borrows, but not both at the same time:

one or more references (&T) to a resource.

exactly one mutable reference (&mut T)

While the rules themselves are simple, following them consistently is not, particularly for those unaccustomed to reasoning about lifetimes and ownership.

The first step in understanding the borrow checker is reading the errors it produces. A lot of work has been put into making sure the borrow checker provides quality assistance in resolving the issues it identifies. When you encounter a borrow checker problem, the first step is to slowly and carefully read the error reported, and to only approach the code after you understand the error being described.

The second step is to become familiar with the ownership and mutability-related container types provided by the Rust standard library, including Cell, RefCell, and Cow. These are useful and necessary tools for expressing certain ownership and mutability situations, and have been written to be of minimal performance cost.

The single most important part of understanding the borrow checker is practice. Rust’s strong static analyses guarantees are strict and quite different from what many programmers have worked with before. It will take some time to become completely comfortable with everything.

If you find yourself struggling with the borrow checker, or running out of patience, always feel free to reach out to the Rust community for help.

This is covered in the official documentation for Rc, Rust’s non-atomically reference-counted pointer type. In short, Rc and its thread-safe cousin Arc are useful to express shared ownership, and have the system automatically deallocate the associated memory when no one has access to it.

To return a closure from a function, it must be a “move closure”, meaning that the closure is declared with the move keyword. As explained in the Rust book, this gives the closure its own copy of the captured variables, independent of its parent stack frame. Otherwise, returning a closure would be unsafe, as it would allow access to variables that are no longer valid; put another way: it would allow reading potentially invalid memory. The closure must also be wrapped in a Box, so that it is allocated on the heap. Read more about this in the book.

A deref coercion is a handy coercion
that automatically converts references to pointers (e.g., &Rc<T> or &Box<T>) into references
to their contents (e.g., &T). Deref coercions exist to make using Rust more ergonomic, and are implemented via the Deref trait.

A Deref implementation indicates that the implementing type may be converted into a target by a call to the deref method, which takes an immutable reference to the calling type and returns a reference (of the same lifetime) to the target type. The * prefix operator is shorthand for the deref method.

If you have a type U, and it implements Deref<Target=T>, values of &U will automatically coerce to a &T.

For example, if you have a &Rc<String>, it will coerce via this rule into a &String, which then coerces to a &str in the same way. So if a function takes a &str parameter, you can pass in a &Rc<String> directly, with all coercions handled automatically via the Deref trait.

The most common sorts of deref coercions are:

&Rc<T> to &T

&Box<T> to &T

&Arc<T> to &T

&Vec<T> to &[T]

&String to &str

Lifetimes

Lifetimes are Rust’s answer to the question of memory safety. They allow Rust to ensure memory safety without the performance costs of garbage collection. They are based on a variety of academic work, which can be found in the Rust book.

The 'a syntax comes from the ML family of programming languages, where 'a is used to indicate a generic type parameter. For Rust, the syntax had to be something that was unambiguous, noticeable, and fit nicely in a type declaration right alongside traits and references. Alternative syntaxes have been discussed, but no alternative syntax has been demonstrated to be clearly better.

You need to ensure that the borrowed item will outlive the function. This can be done by binding the output lifetime to some input lifetime like so:

typePool=TypedArena<Thing>;// (the lifetime below is only written explicitly for// expository purposes; it can be omitted via the// elision rules described in a later FAQ entry)fncreate_borrowed<'a>(pool:&'aPool,x:i32,y:i32)->&'aThing{pool.alloc(Thing{x:x,y:y})}

An alternative is to eliminate the references entirely by returning an owning type like String:

In fact, all reference types have a lifetime, but most of the time you do not have to write
it explicitly. The rules are as follows:

Within a function body, you never have to write a lifetime explicitly; the correct value
should always be inferred.

Within a function signature (for example, in the types of its
arguments, or its return type), you may have to write a lifetime
explicitly. Lifetimes there use a simple defaulting scheme called
“lifetime elision”,
which consists of the following three rules:

Each elided lifetime in a function’s arguments becomes a distinct lifetime parameter.

If there is exactly one input lifetime, elided or not, that
lifetime is assigned to all elided lifetimes in the return values
of that function.

If there are multiple input lifetimes, but one of them is &self
or &mut self, the lifetime of self is assigned to all elided
output lifetimes.

Finally, in a struct or enum definition, all lifetimes must be explicitly declared.

If these rules result in compilation errors, the Rust compiler will provide an error message indicating the error caused, and suggesting a potential solution based on which step of the inference process caused the error.

The only way to construct a value of type &Foo or &mut Foo is to specify an existing value of type Foo that the reference points to. The reference “borrows” the original value for a given region of code (the lifetime of the reference), and the value being borrowed from cannot be moved or destroyed for the duration of the borrow.

Generics

Monomorphisation specializes each use of a generic function (or structure) with specific instance,
based on the parameter types of calls to that function (or uses of the structure).

During monomorphisation a new copy of the generic function is translated for each unique set of types the function is instantiated with. This is the same strategy used by C++. It results in fast code that is specialized for every call-site and statically dispatched, with the tradeoff that functions instantiated with many different types can cause “code bloat”, where multiple function instances result in larger binaries than would be created with other translation strategies.

Functions that accept trait objects instead of type parameters do not undergo monomorphisation. Instead, methods on the trait objects are dispatched dynamically at runtime.

Functions and closures are operationally equivalent, but have different runtime representations due to their differing implementations.

Functions are a built-in primitive of the language, while closures are essentially syntactic sugar for one of three traits: Fn, FnMut, and FnOnce. When you make a closure, the Rust compiler automatically creates a struct implementing the appropriate trait of those three and containing the captured environment variables as members, and makes it so the struct can be called as a function. Bare functions can not capture an environment.

The big difference between these traits is how they take the self parameter. Fn takes &self, FnMut takes &mut self, and FnOnce takes self.

Even if a closure does not capture any environment variables, it is represented at runtime as two pointers, the same as any other closure.

Higher-kinded types are types with unfilled parameters. Type constructors, like Vec, Result, and HashMap are all examples of higher-kinded types: each requires some additional type parameters in order to actually denote a specific type, like Vec<u32>. Support for higher-kinded types means these “incomplete” types may be used anywhere “complete” types can be used, including as generics for functions.

Any complete type, like i32, bool, or char is of kind * (this notation comes from the field of type theory). A type with one parameter, like Vec<T> is of kind * -> *, meaning that Vec<T> takes in a complete type like i32 and returns a complete type Vec<i32>. A type with three parameters, like HashMap<K, V, S> is of kind * -> * -> * -> *, and takes in three complete types (like i32, String, and RandomState) to produce a new complete type HashMap<i32, String, RandomState>.

In addition to these examples, type constructors can take lifetime arguments, which we’ll denote as Lt. For example, slice::Iter has kind Lt -> * -> *, because it must be instantiated like Iter<'a, u32>.

The lack of support for higher-kinded types makes it difficult to write certain kinds of generic code. It’s particularly problematic for abstracting over concepts like iterators, since iterators are often parameterized over a lifetime at least. That in turn has prevented the creation of traits abstracting over Rust’s collections.

Another common example is concepts like functors or monads, both of which are type constructors, rather than single types.

Rust doesn’t currently have support for higher-kinded types because it hasn’t been a priority compared to other improvements we want to make. Since the design is a major, cross-cutting change, we also want to approach it carefully. But there’s no inherent reason for the current lack of support.

These are called associated types, and they allow for the expression of trait bounds that can’t be expressed with a where clause. For example, a generic bound X: Bar<T=Foo> means “X must implement the trait Bar, and in that implementation of Bar, X must choose Foo for Bar’s associated type, T.” Examples of where such a constraint cannot be expressed via a where clause include trait objects like Box<Bar<T=Foo>>.

Associated types exist because generics often involve families of types, where one type determines all of the others in a family. For example, a trait for graphs might have as its Self type the graph itself, and have associated types for nodes and for edges. Each graph type uniquely determines the associated types. Using associated types makes it much more concise to work with these families of types, and also provides better type inference in many cases.

There are some types in Rust whose values are only partially ordered, or have only partial equality. Partial ordering means that there may be values of the given type that are neither less than nor greater than each other. Partial equality means that there may be values of the given type that are not equal to themselves.

Floating point types (f32 and f64) are good examples of each. Any floating point type may have the value NaN (meaning “not a number”). NaN is not equal to itself (NaN == NaN is false), and not less than or greater than any other floating point value. As such, both f32 and f64 implement PartialOrd and PartialEq but not Ord and not Eq.

As explained in the earlier question on floats, these distinctions are important because some collections rely on total orderings/equality in order to give correct results.

The File type implements the Read trait, which has a variety of functions for reading and writing data, including read(), read_to_end(), bytes(), chars(), and take(). Each of these functions reads a certain amount of input from a given file. read() reads as much input as the underlying system will provide in a single call. read_to_end() reads the entire buffer into a vector, allocating as much space as is needed. bytes() and chars() allow you to iterate over the bytes and characters of the file, respectively. Finally, take() allows you to read up to an arbitrary number of bytes from the file. Collectively, these should allow you to efficiently read in any data you need.

For buffered reads, use the BufReader struct, which helps to reduce the number of system calls when reading.

unwrap() is a function that extracts the value inside an Option or Result and panics if no value is present.

unwrap() shouldn’t be your default way to handle errors you expect to arise, such as incorrect user input. In production code, it should be treated like an assertion that the value is non-empty, which will crash the program if violated.

It’s also useful for quick prototypes where you don’t want to handle an error yet, or blog posts where error handling would distract from the main point.

It’s probably an issue with the function’s return type. The try! macro either extracts the value from a Result, or returns early with the error Result is carrying. This means that try only works for functions that return Result themselves, where the Err-constructed type implements From::from(err). In particular, this means that the try! macro cannot work inside the main function.

If you’re looking for a way to avoid handling Results in other people’s code, there’s always unwrap(), but it’s probably not what you want. Result is an indicator that some computation may or may not complete successfully. Requiring you to handle these failures explicitly is one of the ways that Rust encourages robustness. Rust provides tools like the try! macro to make handling failures ergonomic.

If you really don’t want to handle an error, use unwrap(), but know that doing so means that the code panics on failure, which usually results in a shutting down the process.

Concurrency

Mutation is safe if it’s synchronized. Mutating a static Mutex (lazily initialized via the lazy-static crate) does not require an unsafe block, nor does mutating a static AtomicUsize (which can be initialized without lazy_static).

Macros

Not currently. Rust macros are “hygienic macros”, which intentionally avoid capturing or creating identifiers that may cause unexpected collisions with other identifiers. Their capabilities are significantly different than the style of macros commonly associated with the C preprocessor. Macro invocations can only appear in places where they are explicitly supported: items, method declarations, statements, expressions, and patterns. Here, “method declarations” means a blank space where a method can be put. They can’t be used to complete a partial method declaration. By the same logic, they can’t be used to complete a partial variable declaration.

Debugging and Tooling

Rust programs can be debugged using gdb or lldb, the same as C and C++. In fact, every Rust installation comes with one or both of rust-gdb and rust-lldb (depending on platform support). These are wrappers over gdb and lldb with Rust pretty-printing enabled.

This error is usually caused by unwrap()ing a None or Err in client code. Enabling backtraces by setting the environment variable RUST_BACKTRACE=1 helps with getting more information. Compiling in debug mode (the default for cargo build) is also helpful. Using a debugger like the provided rust-gdb or rust-lldb is also helpful.

Low-Level

To copy potentially overlapping bytes, use copy. To copy nonoverlapping bytes, use copy_nonoverlapping. Both of these functions are unsafe, as both can be used to subvert the language’s safety guarantees. Take care when using them.

Absolutely. Rust programs can be set to not load the standard library using the #![no_std] attribute. With this attribute set, you can continue to use the Rust core library, which is nothing but the platform-agnostic primitives. As such, it doesn’t include IO, concurrency, heap allocation, etc.

Not by default. In the general case, enum and struct layouts are undefined. This allows the compiler to potentially do optimizations like re-using padding for the discriminant, compacting variants of nested enums, reordering fields to remove padding, etc. enums which carry no data (“C-like”) are eligible to have a defined representation. Such enums are easily distinguished in that they are simply a list of names that carry no data:

enumCLike{A,B=32,C=34,D}

The #[repr(C)] attribute can be applied to such enums to give them the same representation they would have in equivalent C code. This allows using Rust enums in FFI code where C enums are also used, for most use cases. The attribute can also be applied to structs to get the same layout as a C struct would.

Cross compilation is possible in Rust, but it requires a bit of work to set up. Every Rust compiler is a cross-compiler, but libraries need to be cross-compiled for the target platform.

Rust does distribute copies of the standard library for each of the supported platforms, which are contained in the rust-std-* files for each of the build directories found on the distribution page, but there are not yet automated ways to install them.

There are a number of possible answers, but a common mistake is not realizing that use declarations are relative to the crate root. Try rewriting your declarations to use the paths they would use if defined in the root file of your project and see if that fixes the problem.

There are also self and super, which disambiguate use paths as being relative to the current module or parent module, respectively.

There are two ways to declare modules in Rust, inline or in another file. Here is an example of each:

// In main.rsmodhello{pubfnf(){println!("hello!");}}fnmain(){hello::f();}

// In main.rsmodhello;fnmain(){hello::f();}// In hello.rspubfnf(){println!("hello!");}

In the first example, the module is defined in the same file it’s used. In the second example, the module declaration in the main file tells the compiler to look for either hello.rs or hello/mod.rs, and to load that file.

Note the difference between mod and use: mod declares that a module exists, whereas use references a module declared elsewhere, bringing its contents into scope within the current module.

For methods defined on a trait, you have to explicitly import the trait declaration. This means it’s not enough to import a module where a struct implements the trait, you must also import the trait itself.

It probably could, but you also don’t want it to. While in many cases it is likely that the compiler could determine the correct module to import by simply looking for where a given identifier is defined, this may not be the case in general. Any decision rule in rustc for choosing between competing options would likely cause surprise and confusion in some cases, and Rust prefers to be explicit about where names are coming from.

For example, the compiler could say that in the case of competing identifier definitions the definition from the earliest imported module is chosen. So if both module foo and module bar define the identifier baz, but foo is the first registered module, the compiler would insert use foo::baz;.

modfoo;modbar;// use foo::baz // to be inserted by the compiler.fnmain(){baz();}

If you know this is going to happen, perhaps it saves a small number of keystrokes, but it also greatly increases the possibility for surprising error messages when you actually meant for baz() to be bar::baz(), and it decreases the readability of the code by making the meaning of a function call dependent on module declaration. These are not tradeoffs we are willing to make.

However, in the future, an IDE could help manage declarations, which gives you the best of both worlds: machine assistance for pulling in names, but explicit declarations about where those names are coming from.

In the first month with crates.io, a number of people have asked us about the possibility of introducing namespaced packages.

While namespaced packages allow multiple authors to use a single, generic name, they add complexity to how packages are referenced in Rust code and in human communication about packages. At first glance, they allow multiple authors to claim names like http, but that simply means that people will need to refer to those packages as wycats' http or reem's http, offering little benefit over package names like wycats-http or reem-http.

When we looked at package ecosystems without namespacing, we found that people tended to go with more creative names (like nokogiri instead of “tenderlove’s libxml2”). These creative names tend to be short and memorable, in part because of the lack of any hierarchy. They make it easier to communicate concisely and unambiguously about packages. They create exciting brands. And we’ve seen the success of several 10,000+ package ecosystems like NPM and RubyGems whose communities are prospering within a single namespace.

In short, we don’t think the Cargo ecosystem would be better off if Piston chose a name like bvssvni/game-engine (allowing other users to choose wycats/game-engine) instead of simply piston.

Because namespaces are strictly more complicated in a number of ways, and because they can be added compatibly in the future should they become necessary, we’re going to stick with a single shared namespace.

Libraries

The standard library does not include an implementation of HTTP, so you will want to use an external crate.
reqwest is the simplest.
It is built on hyper, and written in Rust, but there are a number of others as well.
The curl crate is widely used and provides bindings to the curl library.

That depends. There are ways of translating object-oriented concepts like multiple inheritance to Rust, but as Rust is not object-oriented the result of the translation may look substantially different from its appearance in an OO language.

The easiest way is to use the Option type in whatever function you’re using to construct instances of the struct (usually new()). Another way is to use the builder pattern, where only certain functions instantiating member variables must be called before the construction of the built type.

Globals in Rust can be done using const declarations for compile-time computed global constants, while static can be used for mutable globals. Note that modifying a static mut variable requires the use of unsafe, as it allows for data races, one of the things guaranteed not to happen in safe Rust. One important distinction between const and static values is that you can take references to static values, but not references to const values, which don’t have a specified memory location. For more information on const vs. static, read the Rust book.

Rust currently has limited support for compile time constants. You can define primitives using const declarations (similar to static, but immutable and without a specified location in memory) as well as define const functions and inherent methods.

To define procedural constants that can’t be defined via these mechanisms, use the lazy-static crate, which emulates compile-time evaluation by automatically evaluating the constant at first use.

Rust has no concept of “life before main”. The closest you’ll see can be done through the lazy-static crate, which simulates a “before main” by lazily initializing static variables at their first usage.

No. Globals cannot have a non-constant-expression constructor and cannot have a destructor at all. Static constructors are undesirable because portably ensuring a static initialization order is difficult. Life before main is often considered a misfeature, so Rust does not allow it.

See the C++ FQA about the “static initialization order fiasco”, and Eric Lippert’s blog for the challenges in C#, which also has this feature.

You can approximate non-constant-expression globals with the lazy-static crate.

There are several factors that contribute to Rust programs having, by default, larger binary sizes than functionally-equivalent C programs. In general, Rust’s preference is to optimize for the performance of real-world programs, not the size of small programs.

Monomorphization

Rust monomorphizes generics, meaning that a new version of a generic function or type is generated for each concrete type it’s used with in the program. This is similar to how templates work in C++. For example, in the following program:

Two distinct versions of foo will be in the final binary, one specialized to an i32 input, one specialized to a &str input. This enables efficient static dispatch of the generic function, but at the cost of a larger binary.

Debug symbols

Rust programs compile with some debug symbols retained, even when compiling in release mode. These are used for providing backtraces on panics, and can be removed with strip, or another debug symbol removal tool. It is also useful to note that compiling in release mode with Cargo is equivalent to setting optimization level 3 with rustc. An alternative optimization level (called s or z) has recently landed and tells the compiler to optimize for size rather than performance.

Jemalloc

Rust uses jemalloc as the default allocator, which adds some size to compiled Rust binaries. Jemalloc is chosen because it is a consistent, quality allocator that has preferable performance characteristics compared to a number of common system-provided allocators. There is work being done to make it easier to use custom allocators, but that work is not yet finished.

Link-time optimization

Rust does not do link-time optimization by default, but can be instructed to do so. This increases the amount of optimization that the Rust compiler can potentially do, and can have a small effect on binary size. This effect is likely larger in combination with the previously mentioned size optimizing mode.

Standard library

The Rust standard library includes libbacktrace and libunwind, which may be undesirable in some programs. Using #![no_std] can thus result in smaller binaries, but will also usually result in substantial changes to the sort of Rust code you’re writing. Note that using Rust without the standard library is often functionally closer to the equivalent C code.

As an example, the following C program reads in a name and says “hello” to the person with that name.

This program, when compiled and compared against the C program, will have a larger binary and use more memory. But this program is not exactly equivalent to the above C code. The equivalent Rust code would instead look something like this:

Committing to an ABI is a big decision that can limit potentially advantageous language changes in the future. Given that Rust only hit 1.0 in May of 2015, it is still too early to make a commitment as big as a stable ABI. This does not mean that one won’t happen in the future, though. (Though C++ has managed to go for many years without specifying a stable ABI.)

The extern keyword allows Rust to use specific ABI’s, such as the well-defined C ABI, for interop with other languages.

Yes. The Rust code has to be exposed via an extern declaration, which makes it C-ABI compatible. Such a function can be passed to C code as a function pointer or, if given the #[no_mangle] attribute to disable symbol mangling, can be called directly from C code.

Modern C++ includes many features that make writing safe and correct code less error-prone, but it’s not perfect, and it’s still easy to introduce unsafety. This is something the C++ core developers are working to overcome, but C++ is limited by a long history that predates a lot of the ideas they are now trying to implement.

Rust was designed from day one to be a safe systems programming language, which means it’s not limited by historic design decisions that make getting safety right in C++ so complicated. In C++, safety is achieved by careful personal discipline, and is very easy to get wrong. In Rust, safety is the default. It gives you the ability to work in a team that includes people less perfect than you are, without having to spend your time double-checking their code for safety bugs.

The underlying concepts are similar, but the two systems work very
differently in practice. In both systems, “moving” a value is a way to
transfer ownership of its underlying resources. For example, moving a
string would transfer the string’s buffer rather than copying it.

In Rust, ownership transfer is the default behavior. For example, if I
write a function that takes a String as argument, this function will
take ownership of the String value supplied by its caller:

As you can see in the snippet above, in the function caller, the
first call to process transfers ownership of the variable s. The
compiler tracks ownership, so the second call to process results in
an error, because it is illegal to give away ownership of the same
value twice. Rust will also prevent you from moving a value if there
is an outstanding reference into that value.

C++ takes a different approach. In C++, the default is to copy a value
(to invoke the copy constructor, more specifically). However, callees
can declare their arguments using an “rvalue reference”, like
string&&, to indicate that they will take ownership of some of the
resources owned by that argument (in this case, the string’s internal
buffer). The caller then must either pass a temporary expression or
make an explicit move using std::move. The rough equivalent to the
function process above, then, would be:

C++ compilers are not obligated to track moves. For example, the code
above compiles without a warning or error, at least using the default
settings on clang. Moreover, in C++ ownership of the string s itself
(if not its internal buffer) remains with caller, and so the
destructor for s will run when caller returns, even though it has
been moved (in Rust, in contrast, moved values are dropped only by
their new owners).

Rust and C++ can interoperate through C. Both Rust and C++ provide a foreign function interface for C, and can use that to communicate between each other. If writing C bindings is too tedious, you can always use rust-bindgen to help automatically generate workable C bindings.

No. Functions serve the same purpose as constructors without adding language complexity. The usual name for the constructor-equivalent function in Rust is new(), although this is just a convention rather than a language rule. The new() function in fact is just like any other function. An example of it looks like so:

Not exactly. Types which implement Copy will do a standard C-like “shallow copy” with no extra work (similar to trivially copyable types in C++). It is impossible to implement Copy types that require custom copy behavior. Instead, in Rust “copy constructors” are created by implementing the Clone trait, and explicitly calling the clone method. Making user-defined copy operators explicit surfaces the underlying complexity, making it easier for the developer to identify potentially expensive operations.

Rust and Go have substantially different design goals. The following differences are not the only ones (which are too numerous to list), but are a few of the more important ones:

Rust is lower level than Go. For example, Rust does not require a garbage collector, whereas Go does. In general, Rust affords a level of control that is comparable to C or C++.

Rust’s focus is on ensuring safety and efficiency while also providing high-level affordances, while Go’s is on being a small, simple language which compiles quickly and can work nicely with a variety of tools.

Rust has strong support for generics, which Go does not.

Rust has strong influences from the world of functional programming, including a type system which draws from Haskell’s typeclasses. Go has a simpler type system, using interfaces for basic generic programming.

Rust’s impl resolution considers the relevant where clauses and trait bounds when deciding whether two impls overlap, or choosing between potential impls. Haskell only considers the constraints in the instance declaration, disregarding any constraints provided elsewhere.

A subset of Rust’s traits (the “object safe” ones) can be used for dynamic dispatch via trait objects. The same feature is available in Haskell via GHC’s ExistentialQuantification.

Documentation

The Rust language has been around for a number of years, and only reached version 1.0 in May of 2015. In the time before then the language changed significantly, and a number of Stack Overflow answers were given at the time of older versions of the language.

Over time more and more answers will be offered for the current version, thus improving this issue as the proportion of out-of-date answers is reduced.

When you use cargo doc to generate documentation for your own project, it also generates docs for the active dependency versions. These are put into the target/doc directory of your project. Use cargo doc --open to open the docs after building them, or just open up target/doc/index.html yourself.